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Biomedical engineering International Conference (BMEiCON)

作者： Patcharapon Kangwarnchokchai Boonchai Techaumnat Noppadon Nuntawong Kenji Mishima Tanjina Sharmin Taku Michael Aida Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Dept. of Electrical Engineering and Biomedical Research Center Faculty of Engineering Chulalongkorn University Bangkok Thailand Spectroscopic and Sensing Devices Research Group National Electronics and Computer Technology Center Pathumthani Thailand Department of Chemical Engineering Faculty of Engineering Fukuoka University Fukuoka Japan

ISBN: (纸本)9781665489041

This paper presents the electroporation of canine MCT cells by a low voltage in microfluidic system. We examined the electroporation efficiency with pulse conditions and correlated the results from the impedance measurement to the membrane openings. Dielectrophoretic force was applied to position the cell at a desired location. Temporary and permanent electroporation cells was discriminated by using a combination of Yo-Pro-1 and propidium iodide (PI) fluorescent dyes. From the experiment, we determined the appropriate condition for the reversible electroporation of the canine MCT cells to be 15 sets of $2.5 \mathrm{V}_{p}$, 20kHz frequency, and 50-cycle pulses. The condition yielded 50% efficiency for the reversible electroporation. In addition, the area of the cell-membrane pores could be quantitatively examined from the conductance measured without a cell and those with a cell before and after applying electroporation pulses.

关键词： Low voltage Iodine compounds Impedance measurement Pulse measurements Force Estimation Fluorescence

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Power law susceptibility function for the analysis of anomalous spectral response

arXiv

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arXiv 2024年

作者： Allagui, Anis Balaguera, Enrique H. Dept. of Sustainable and Renewable Energy Engineering University of Sharjah Sharjah Sharjah27272 United Arab Emirates Center for Advanced Materials Research Research Institute of Sciences and Engineering University of Sharjah Sharjah Sharjah27272 United Arab Emirates Dept. of Electrical and Computer Engineering Florida International University MiamiFL33174 United States Escuela Superior de Ciencias Experimentales y Tecnologia Universidad Rey Juan Carlos C/ Tulipan s/n Mostoles Madrid28933 Spain

The extensions of the classical Debye model of susceptibility of dielectric materials to the well-known Cole-Cole, Davidson-Cole, or the Havriliak-Negami models is done by introducing non-integer power parameters to the frequency-domain function. This is very often necessary in order to account for anomalous deviations of the experimental data from the ideal case. The corresponding time-domain descriptions expressed in terms of the relaxation or response functions are in the form of first-order differential equations for the case of Debye model, but involves relatively complex integro-differential operators for the modified ones. In this work, we study the extension of the time-domain kinetic equation describing the Debye polarization function to include two extra degrees of freedom;one to transform the first-order time derivative of the polarization function to the Caputo fractional-order time derivative and another to change the linear term to a power term. From an electrical perspective, it results in a constant-phase element with two fractional parameters. © 2024, CC BY.

关键词： Frequency domain analysis

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Growth Chemistry of Nanocrystalline Si:H Films

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MRS Online Proceedings Library 2020年第1期862卷 2141-2146页

作者： Vikram L. Dalal Kamal Muthukrishnan Daniel Stieler Max Noack Dept. of Electrical and Computer Engr. Microelectronics Research Center Ames USA

We report on the growth of nanocrystalline Si:H films using both plasma CVD and remote hot wire deposition under systematically varied growth conditions. The films were grown from mixtures of silane and hydrogen. It was found that when the films were grown under low pressure VHF plasma growth conditions, the orientation of the film changed as the pressure increased. At the lowest pressures, the films were mainly <111> oriented, but changed to <220> orientation as the pressure increased. The grain size increased as the growth temperature increased. When the films were grown using remote hot wire deposition, the orientation depended upon both hydrogen dilution and growth temperature. As the hydrogen dilution increased, the <220> grain size became smaller. Grain size as large as 36 nm was obtained by controlling the growth conditions in hot wire deposition. As the growth temperature increased, the size of <220> grains increased. Growth rates also increased with increasing temperature. The data can be explained by invoking a growth model which recognizes that the natural growth direction for Si is <220>, since the surface energy is highest for (220) plane. Random nucleation leads to <111> grains. Bonded H is believed to inhibit the growth of <220> grains.

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Sparse Gaussian Process Regression using Progressively Growing Learning Representations

Sparse Gaussian Process Regression using Progressively Growi...

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IEEE Conference on Decision and Control

作者： Christos N. Mavridis George P. Kontoudis John S. Baras Department of Electrical and Computer Engineering Institute for Systems Research University of Maryland College Park USA Dept. of Aerospace Engineering Maryland Robotics Center Inst. of Systems Research University of Maryland College Park MD USA

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

We present a new sparse Gaussian process regression model whose covariance function is parameterized by the locations of a progressively growing set of pseudo-inputs generated by an online deterministic annealing optimization algorithm. A series of entropy-regularized optimization problems is solved sequentially, introducing a bifurcation phenomenon, according to which, pseudo-inputs are gradually generated. This results in an active learning approach, which, in contrast to most existing works, can modify already selected pseudo-inputs and is trained using a recursive gradient-free stochastic approximation algorithm. Finally, the proposed algorithm is able to incorporate prior knowledge in the form of a probability density, according to which new observations are sampled. Experimental results showcase the efficacy and potential advantages of the proposed methodology.

关键词： Annealing Gaussian processes Bifurcation Approximation algorithms Optimization

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In-vivo 3D zebrafish imaging for longitudinal observation of the retina regeneration with different light intensity irradiations 31

In-vivo 3D zebrafish imaging for longitudinal observation of...

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Ophthalmic Technologies XXXI 2021

作者： Jo, Hang Chan Kim, Dae Yu Measurement Engineering Laboratory Dept. of Electrical and Computer Engineering Inha University Incheon22212 Korea Republic of Center for Sensor Systems College of Engineering Inha University Incheon22212 Korea Republic of Inha Research Institute for Aerospace Medicine Inha University Incheon22212 Korea Republic of

ISBN: (数字)9781510640825

ISBN: (纸本)9781510640818

The retina regeneration process has been observed in several animals including fish, birds, and amphibians, whereas the injured human retina cannot regenerate until today. The zebrafish is one of the animals which can regenerate their retina. Due to similarities between humans and the zebrafish in the morphology of the eye as well as the gene, the zebrafish has been chosen as a useful model for investigating retina regeneration. Previous studies have observed morphological changes in the zebrafish retina using optical coherence tomography during the retinal regeneration after light irradiation with a single beam power. However, these studies have limitations of demonstrating differences in regenerative abilities depending on degrees of retinal damages because they used only a single light irradiating condition. Through light-induced retinal injuries by various light irradiating conditions, investigation correlations between the time required for retina regeneration and grades of retinal damages were needed. To conduct these experiments, a custom-built OCT, which can acquire a cross-sectional and three-dimensional image of the zebrafish's eye, was developed based on OpticStudio® simulations. The zebrafish's eye imaging can provide the ability to observe the damage and morphological changes after laser irradiation in the eye tissues including the cornea and retina. © 2021 SPIE.

关键词： Optical tomography

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A Decision-Dependent Chance-Constrained Planning Model for Distribution Networks Under Extreme Weather Events

A Decision-Dependent Chance-Constrained Planning Model for D...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Anping Zhou Hongbo Sun Shoichi Kitamura Daniel Nikovski Dept. of Electrical and Computer Engineering Southern Methodist University Dallas TX USA Advanced Technology R&D Center Mitsubishi Electric Corporation Amagasaki Japan Data Analytics Group Mitsubishi Electric Research Laboratories Cambridge MA USA

Extreme weather events have posed tremendous challenges to the operation of distribution networks. In this paper, we propose a decision-dependent chance-constrained model for the optimal planning of diesel generators, renewable distributed generations (RDGs), energy storage systems, and switches under contingency. A promising moment-based ambiguity set that incorporates the information of decision variables is employed to depict the uncertainty arising from RDGs. By leveraging effective approximation methods such as the Bonferroni approximation method to handle the considered joint chance constraints, the proposed model is transformed into a tractable mixed-integer second-order conic programming problem, which means it can easily be implemented. Numerical experiments are put forward on the IEEE 33-bus test system to validate the effectiveness of the developed approach.

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Solving water scarcity challenges in arid regions: A novel approach employing human-based meta-heuristics and machine learning algorithm for groundwater potential mapping

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Chemosphere 2024年 363卷 142859页

作者： Razavi-Termeh, Seyed Vahid Sadeghi-Niaraki, Abolghasem Farhangi, Farbod Khiadani, Mehdi Pirasteh, Saied Choi, Soo-Mi Dept. of Computer Science & Engineering and Convergence Engineering for Intelligent Drone XR Research Center Sejong University Seoul Korea Republic of Geoinformation Tech. Center of Excellence Faculty of Geodesy and Geomatics Engineering K.N. Toosi University of Technology Tehran19697 Iran School of Engineering Edith Cowan University 270 Joondalup Drive JoondalupWA6027 Australia Institute of Artificial Intelligence School of Mechanical and Electrical Engineering Shaoxing University China Department of Geotechnics and Geomatics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602105 India

Addressing water scarcity challenges in arid regions is a pressing concern and demands innovative solutions for accurate groundwater potential mapping (GPM). This study presents a comprehensive evaluation of advanced modeling techniques to enhance the precision of GPM. This study, conducted in the Zayandeh Rood watershed, Iran, employed a spatial database comprising 16 influential factors on groundwater potential and data from 175 wells. This study introduced an innovative approach to GPM by enhancing the Random Forest (RF) algorithm. This enhancement involved integrating three metaheuristic algorithms inspired by human behavior: ICA (Imperialist Competitive Algorithm), TLBO (Teaching-Learning-Based Optimization), and SBO (Student Psychology Based Optimization). The modeling process used 70% training data and 30% evaluation data. Data preprocessing was performed using the multicollinearity test method and frequency ratio (FR) technique to refine the dataset. Subsequently, the GPM was generated using four distinct models, demonstrating the combined power of machine learning and human-inspired metaheuristic algorithms. The performance of the models was systematically assessed through extensive statistical analyses, including root mean squared error (RMSE), mean absolute error (MAE), area under the curve (AUC) for the receiver operating characteristic curve (ROC), Friedman tests, chi-squared tests, and Wilcoxon signed-rank tests. RF-ICA and RF-SPBO emerged as frontrunners, displaying statistically comparable accuracy and significantly outperforming RF-TLBO and the non-optimized RF model. The results of the GPM revealed the exceptional accuracy of RF-ICA, which exhibited a commanding AUC score of 0.865, underscoring its superiority in discriminating between different groundwater potential classes. RF-SPBO also displayed strong performance with an AUC of 0.842, highlighting its effectiveness in inaccurate classification. RF-TLBO and the non-optimized RF model achieved AU

关键词： Geographic information systems

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Heart Failure: Machine Learning Prediction Within a 5-Year Framework

Heart Failure: Machine Learning Prediction Within a 5-Year F...

引用

IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Konstantina-Helen Tsarapatsani Vasilios D. Tsakanikas Antonis Sakellarios Hans J. Trampisch Efterpi Karapintzou Henrik Rudolf George K. Matsopoulos Dimitrios I. Fotiadis Biomedical Research Institute Foundation for Research and Technology-Hellas Ioannina Greece Department of Medical Informatics Biometry and Epidemiology Ruhr University Bochum Bochum Germany Dept. of Materials Science and Engineering Unit of Medical Technology and Intelligent Information Systems University of Ioannina Greece Institute for Biostatistics and Informatics in Medicine and Ageing Research University Medical Center Rostock Germany School of Electrical and Computer Engineering National Technical University of Athens Athens Greeece Dept. of Materials Science and Engineering Unit of Medical Technology and Intelligent Information Systems University of Ioannina and Biomedical Research Institute-FORTH Ioannina Greece

ISBN: (数字)9798331518622

ISBN: (纸本)9798331518639

Heart failure (HF) is a complex syndrome that is affected by many factors and causes. It is crucial to early recognize the disease subtypes and the unidentified clinical pathways that give rise to it. Machine learning (ML) is the tool that assist to deal with these challenges and improve the prediction of HF. In this work, the HF risk prediction was implemented by employed ML classifiers, such as Random Forest (RF), Extreme Grading Boosting (XGBoost) and Light Gradient-Boosting Machine (LGBM). We utilized the data from the German epidemiological trial on ankle brachial index - getABI cohort, which includes 6,454 patients. The performance of classifiers was estimated by Accuracy (ACC), Sensitivity, Specificity and the area under the receiver operating characteristic curve (AUC) in mean values for each ML classifier. The results were also interpreted using the Explainable artificial intelligence (XAI) approach, the Shapley Additive exPlanations (SHAP) values. Our work reveals that LGBM classifier predict the HF risk within 5 years follow-up in general population with 68 % accuracy. Moreover, the N-terminal pro-B-type natriuretic peptide (NT-proBNP) was identified as the most important feature for HF risk prediction.

关键词： Accuracy Sensitivity Explainable AI Biological system modeling Peptides Receivers Predictive models Indexes Cardiovascular diseases Random forests

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Automatic spinal curvature measurement on ultrasound spine images using Faster R-CNN

arXiv

引用

arXiv 2022年

作者： Liu, Zhichao Qian, Liyue Jing, Wenke Zhou, Desen He, Xuming Lou, Edmond Zheng, Rui School of Information Science and Technology ShanghaiTech University Shanghai China Electrical & Computer Engineering Dept. University of Alberta Canada Shanghai Engineering Research Center of Intelligent Vision and Imaging ShanghaiTech University Shanghai China

Ultrasound spine imaging technique has been applied to the assessment of spine deformity. However, manual measurements of scoliotic angles on ultrasound images are time-consuming and heavily rely on raters' experience. The objectives of this study are to construct a fully automatic framework based on Faster R-CNN for detecting vertebral lamina and to measure the fitting spinal curves from the detected lamina pairs. The framework consisted of two closely linked modules: 1) the lamina detector for identifying and locating each lamina pairs on ultrasound coronal images, and 2) the spinal curvature estimator for calculating the scoliotic angles based on the chain of detected lamina. Two hundred ultrasound images obtained from AIS patients were identified and used for the training and evaluation of the proposed method. The experimental results showed the 76.1% AP on the test set, and the Mean Absolute Difference (MAD) between automatic and manual measurement was 4.3° which was within the clinical acceptance error (5°). Meanwhile the correlation between automatic measurement and Cobb angle from radiographs was 0.79. The results revealed that our proposed technique could provide accurate and reliable automatic curvature measurements on ultrasound spine images for spine deformities. Copyright © 2022, The Authors. All rights reserved.

关键词： Curve fitting

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A silicon-based ion trap chip protected from semiconductor charging

arXiv

引用

arXiv 2024年

作者： Chung, Daun Choi, Kwangyeul Lee, Woojun Kim, Chiyoon Shon, Hosung Park, Jeonghyun Cho, Beomgeun Lee, Kyungmin Kim, Suhan Yoo, Seungwoo Jung, Eui Hwan Jung, Changhyun Kang, Jiyong Kim, Kyunghye Berkis, Roberts Northup, Tracy Cho, Dong-Il Kim, Taehyun Dept. of Computer Science and Engineering Seoul National University Seoul08826 Korea Republic of Automation and Systems Research Institute Seoul National University Seoul08826 Korea Republic of Inter-University Semiconductor Research Center Seoul National University Seoul08826 Korea Republic of Institute of Computer Technology Seoul National University Seoul08826 Korea Republic of Dept. of Experimental Physics University of Innsbruck Technikerstraße 25 Innsbruck6020 Austria Dept. of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Institute of Applied Physics Seoul National University Seoul08826 Korea Republic of NextQuantum Seoul National University Seoul08826 Korea Republic of

Silicon-based ion trap chips can benefit from existing advanced fabrication technologies, such as multi-metal layer techniques for two-dimensional architectures and silicon photonics for the integration of on-chip optical components. However, the scalability of these technologies may be compromised by semiconductor charging, where photogenerated charge carriers produce electric potentials that disrupt ion motion. Inspired by recent studies on charge distribution mechanisms in semiconductors, we developed a silicon-based chip with gold coated on all exposed silicon surfaces. This modification significantly stabilized ion motion compared to a chip without such metallic shielding, a result that underscores the detrimental effects of exposed silicon. With the mitigation of background silicon-induced fields to negligible levels, quantum operations such as sideband cooling and two-ion entangling gates, which were previously infeasible with the unshielded chip, can now be implemented. © 2024, CC BY.

关键词： Silicon photonics

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